GENOMICS AND ENVIRONMENTAL RESEARCH
The first sequence of the entire genome of an organism was published in 1995. Since then, more than 20 entire
genomes have been published; many more are in progress. With the exception of one nematode worm, all of the
published sequences have been from microbes. But what scientists are learning from the analysis of these
microbes is fueling a scientific revolution.
Some of the unanticipated findings were that in the genomes sequenced thus far, about 40 to 60 percent of the
putative genes encode proteins that had not been seen or studied before, and approximately 25 percent of the
putative genes in each organism were unique to that organism. The large number of unknown and unique genes
led to the realization that the number of microbial species thought to exist on Earth had been vastly underestimated:
At most, we have identified only about 0.01 percent of them.
Another startling finding is that relatively large pieces of DNA may be transmitted from microbe to microbeeven
across distantly related phylogenetic domains such as the bacteria and the archaea (Nelson et al. 1999). Movement
of DNA between these groups shatters the long-held assumption of strict linear descent during species
evolution. Systemacists and evolutionary biologists are now developing new algorithms to analyze microbial
evolution that will take into account the lateral transfer of DNA (Pennisi 1999). Scientists are also reevaluating the
evolution of genetic processes and metabolism in this new light. Inclusion of lateral gene transfer may help us
understand the evolution of complex biological processes as well as multicellular organisms.
Thus far, the genomic revolution has touched only the tip of microbial life. We have at least as much to learn from
the genomic analysis of more complex organismswork that is only now just beginningplants, fungi, and
animals, including humans. For environmental biologists, the ability to understand how an organism responds at
the level of the whole genome will open up new areas of analysis of host-pathogen interactions, environmental
stress, evolution of complex traits, population dynamics, and signal transduction at all levels. Ultimately, genomic-scale
analysis should allow us to dramatically improve some predictive models, including those dealing with
community dynamics as a function of environment and genotype:phenotype relationships.